Many enterprises aim to offer content that may be of interest to their customers to improve chances of a sale or to provide an enriched customer experience. The content is typically offered to existing and potential customers of the enterprise on enterprise interaction channels, such as Websites, native mobile applications, social media, and the like. The existing or potential customers of the enterprise visiting such enterprise interaction channels are hereinafter referred to as online visitors.
Typically, the online visitor population is categorized into segments based on age, gender, professional activity, location, etc., to facilitate selection of content to be provided to the online visitors during their visit to the enterprise interaction channels. Selection of content based on such a categorization of the online visitors has several shortcomings. For example, the selected content may not be customized to an individual online visitor's current behavior or preference. In many scenarios, the content provisioned to an online visitor is not what the online visitor may be interested in for his current visit to the enterprise interaction channel, and the online visitor may ignore such content. In some cases, the online visitor may also get frustrated from viewing irrelevant content and may exit the interaction, leading to a loss for the enterprise.
There is a need to provision content that is customized to an individual online visitor's current behavior or preference. Moreover, there is a need to extend such a provisioning of relevant content to scenarios, where sufficient historical visitor interaction data is absent.